Journal of Big Data

Table 3 Classifier accuracy with filtering

From: Improving binary classification using filtering based on k-NN proximity graphs

Classifier	German	Banknote authn.	Haberman	Ionosphere	Seismic bumps	WDBC
DT	0.746	0.981	0.747	0.894	0.933	0.931
LR	0.76	0.99	0.744	0.878	0.934	0.961
NB	0.757	0.841	0.752	0.814	0.927	0.931
SVM	0.761	0.999	0.736	0.929	0.934	0.969
NN	0.747	0.979	0.742	0.863	0.934	0.948
RF	0.743	0.992	0.748	0.922	0.934	0.948
DES-LA	0.768	0.996	0.747	0.928	0.934	0.963

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